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Adaptive Privacy Policy Prediction of User Uploaded Images on Content sharing Sites

机译:内容共享站点上用户上传的图像的自适应隐私策略预测

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User Image sharing social site maintaining privacy has become a major problem, as demonstrated by a recent wave of publicized incidents where users inadvertently shared personal information. In light of these incidents, the need of tools to help users control access to their shared content is apparent. Toward addressing this need an Adaptive Privacy Policy Prediction (A3P) system to help users compose privacy settings for their images. The solution relies on an image classification framework for image categories which may be associated with similar policies and on a policy prediction algorithm to automatically generate a policy for each newly uploaded image, also according to user's social features. Image Sharing takes place both among previously established groups of known people or social circles and also increasingly with people outside the users social circles, for purposes of social discovery-to help them identify new peers and learn about peers interests and social surroundings, Sharing images within online content sharing sites, therefore, may quickly lead to unwanted disclosure. The aggregated information can result in unexpected exposure of one's social environment and lead to abuse of one's personal information.
机译:用户图像共享社交网站维护隐私已成为一个主要问题,最近的一波公开事件表明,用户无意间共享了个人信息。鉴于这些事件,很明显需要工具来帮助用户控制对其共享内容的访问。为了解决这个问题,需要一个自适应隐私策略预测(A3P)系统,以帮助用户为其图像编写隐私设置。该解决方案依赖于图像类别的图像分类框架,该图像类别框架可以与相似的策略相关联,并且依赖于策略预测算法以还根据用户的社交特征针对每个新上传的图像自动生成策略。图像共享不仅发生在先前建立的已知人群或社交圈中,而且也越来越多地与用户社交圈外的人进行,以进行社交发现-帮助他们识别新的同龄人并了解同龄人的兴趣和社交环境,因此,在线内容共享网站可能会迅速导致不必要的泄露。汇总的信息可能会导致一个人的社交环境意外暴露,并导致滥用一个人的个人信息。

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